Finance Market Risk & Volatility Analysis Dashboard

A data analytics project that analyzes stock market performance using historical financial data. The dashboard focuses on daily returns, market volatility, rolling volatility trends, and Monte Carlo simulations to evaluate risk and forecast possible future stock price movements.

Python Pandas NumPy Matplotlib Plotly Yahoo Finance Jupyter Notebook Streamlit GitHub
Daily Returns Chart
Financial dashboard highlighting the stock’s average daily return and overall market volatility to evaluate investment performance and risk behavior.
20-Day Rolling Volatility Chart
Daily Returns Chart Visualization of daily stock return fluctuations showing short-term market volatility and return behavior over time.
20-Day Rolling Volatility Chart
20-Day Rolling Volatility Chart Tracks the changing market volatility over a rolling 20-day period to identify stable and high-risk market phases.
Monte Carlo Simulation Chart
Monte Carlo Simulation Chart Probability-based simulation of multiple future stock price paths used for forecasting and risk estimation.

Problem Statement

Financial markets are highly volatile, making it difficult for investors and analysts to understand market risk and predict future stock behavior.

The goal of this project is to:

  • Analyze stock return patterns
  • Measure market volatility
  • Identify risk trends over time
  • Simulate future stock prices using probabilistic forecasting methods

Approach (Short)

  • Collected historical stock market data using financial APIs.
  • Cleaned and preprocessed the dataset for time-series analysis.
  • Calculated daily returns and volatility metrics to measure market fluctuations.
  • Performed rolling volatility analysis to identify risk trends over time.
  • Applied Monte Carlo Simulation to forecast multiple possible future stock price movements.
  • Visualized insights through interactive charts and dashboards for better financial analysis.

Concepts & Skills Applied

Financial Data Analysis
Time Series Analysis
Risk Analysis
Volatility Measurement
Monte Carlo Simulation
Interactive Dashboard
Probability & Forecasting

Key Insights

  • Daily returns fluctuate frequently, showing continuous market uncertainty.
  • Certain periods experienced higher volatility spikes, indicating increased investment risk.
  • Rolling volatility decreased in some phases, suggesting temporary market stability.
  • Monte Carlo simulations showed multiple future price possibilities rather than a single fixed prediction.
  • The stock demonstrates moderate volatility overall, meaning both growth opportunities and risk exist.

Business Recommendations & Impact

Recommendations

  • Investors should monitor volatility before making short-term trading decisions.
  • During high-volatility periods, risk management strategies should be strengthened.
  • Monte Carlo forecasting can help investors estimate potential future outcomes before investing.
  • Long-term investment strategies may reduce the impact of short-term market fluctuations.

Business Impact

  • Helps investors make data-driven decisions
  • Supports portfolio risk assessment
  • Improves understanding of market behavior
  • Assists in financial forecasting and investment planning

Features

  • Interactive financial dashboard
  • Daily return analysis
  • Volatility tracking
  • Rolling volatility calculation
  • Monte Carlo future price simulation
  • Time-series visualizations
  • Risk forecasting analytics
VIEW LIVE APP GITHUB REPOSITORY ← BACK TO ALL PROJECTS